ToF相机的有效深度数据提取与校正算法研究

乔欣; 葛晨阳; 邓鹏超; 周艳辉; 姚慧敏

doi:10.11959/j.issn.2096-6652.202008

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ToF相机的有效深度数据提取与校正算法研究

学术论文 | 更新时间：2024-06-05

- ToF相机的有效深度数据提取与校正算法研究
- Research on valid depth data extraction and correction for ToF camera
- 智能科学与技术学报 2020年2卷第1期页码：72-79
- 作者机构：
- 作者简介：
  
  [ "乔欣（1990– ），男，西安交通大学博士生，主要研究方向为计算机视觉、3D 感知和多传感融合" ]
  [ "葛晨阳（1977– ），男，博士，西安交通大学副教授，主要研究方向为计算视觉、三维感知、SoC设计" ]
  [ "邓鹏超（1990– ），男，西安交通大学硕士生，主要研究方向为计算视觉和深度学习" ]
  [ "周艳辉（1981– ），女，博士，西安交通大学副教授，主要研究方向为智能信号处理、反问题方法研究及应用" ]
  [ "姚慧敏（1986– ），女，博士，西安交通大学讲师，主要研究方向为计算机视觉、结构光成像和图像处理" ]
- 基金信息：
  
  国家重大科研仪器研制基金资助项目;The National Important Development Program on Scientific Research Instruments(61627811);国家自然科学基金资助项目;The National Natural Science Foundation of China(61571358)
- DOI：10.11959/j.issn.2096-6652.202008
  中图分类号： TP751
- 网络出版日期：2020-03，
  
  纸质出版日期：2020-03-20
- 稿件说明：
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乔欣, 葛晨阳, 邓鹏超, 等. ToF相机的有效深度数据提取与校正算法研究[J]. 智能科学与技术学报, 2020,2(1):72-79.

Xin QIAO, Chenyang GE, Pengchao DENG, et al. Research on valid depth data extraction and correction for ToF camera[J]. Chinese journal of intelligent science and technology, 2020, 2(1): 72-79.
乔欣, 葛晨阳, 邓鹏超, 等. ToF相机的有效深度数据提取与校正算法研究[J]. 智能科学与技术学报, 2020,2(1):72-79. DOI： 10.11959/j.issn.2096-6652.202008.

Xin QIAO, Chenyang GE, Pengchao DENG, et al. Research on valid depth data extraction and correction for ToF camera[J]. Chinese journal of intelligent science and technology, 2020, 2(1): 72-79. DOI： 10.11959/j.issn.2096-6652.202008.

摘要

提出一种针对 ToF 相机的有效深度数据提取与校正算法，利用深度图和置信度图对深度信息进行校正。首先，基于核密度估计和连通域标记对测得的深度图进行自适应分割；然后使用一种改进的结构张量进行边缘检测，从而探测深度图中的无效像素和飞行像素；最后用双三次方插值或投票操作纠正或剔除这些像素，同时使用增强置信度剔除错误像素。实验结果证明了该算法的有效性，对比传统方法，本文所提算法可以剔除更多的无效像素，且保留更多的有效深度数据，对于噪声的鲁棒性也更好。

Abstract

An algorithm was proposed to extract the valid depth information and correct the values of flying pixels with depth map and confidence map for time-of-flight camera.Firstly

the depth map was segmented adaptively based on kernel density estimation and connected component labeling.Then edge detection was performed by using a modified structure tensor to recognize the invalid pixels and the flying pixels.At last

the values of flying pixels were corrected with the bi-cubic interpolation and that of the invalid pixels were deleted by voting.Meanwhile

using augmented confidence

the pixels with wrong depth values were removed.Experimental results show the effectiveness of the proposed algorithm.Comparing with the conventional methods

the proposed algorithm can remove more invalid pixels and remain more valid depth data.Also

the proposed method is more robust to noise.

关键词

Keywords

references

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